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» Expectation Maximization for Weakly Labeled Data
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IJCAI
2003
13 years 7 months ago
Semi-Supervised Learning with Explicit Misclassification Modeling
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Massih-Reza Amini, Patrick Gallinari
MICCAI
2004
Springer
14 years 6 months ago
Coupling Statistical Segmentation and PCA Shape Modeling
This paper presents a novel segmentation approach featuring shape constraints of multiple structures. A framework is developed combining statistical shape modeling with a maximum a...
Kilian M. Pohl, Simon K. Warfield, Ron Kikinis, W....
CVPR
2009
IEEE
15 years 22 days ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
AAAI
1998
13 years 7 months ago
Learning to Classify Text from Labeled and Unlabeled Documents
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
UIST
2010
ACM
13 years 3 months ago
Mixture model based label association techniques for web accessibility
An important aspect of making the Web accessible to blind users is ensuring that all important web page elements such as links, clickable buttons, and form fields have explicitly ...
Muhammad Asiful Islam, Yevgen Borodin, I. V. Ramak...